Flocks, herds and schools: A distributed behavioral model
SIGGRAPH '87 Proceedings of the 14th annual conference on Computer graphics and interactive techniques
Frontier-based exploration using multiple robots
AGENTS '98 Proceedings of the second international conference on Autonomous agents
Coverage for robotics – A survey of recent results
Annals of Mathematics and Artificial Intelligence
Decision-Theoretic Planning for Autonomous Robotic Surveillance
Applied Intelligence
An Incremental Self-Deployment Algorithm for Mobile Sensor Networks
Autonomous Robots
Coordination for Multi-Robot Exploration and Mapping
Proceedings of the Seventeenth National Conference on Artificial Intelligence and Twelfth Conference on Innovative Applications of Artificial Intelligence
A frontier-based approach for autonomous exploration
CIRA '97 Proceedings of the 1997 IEEE International Symposium on Computational Intelligence in Robotics and Automation
Potential field method to navigate several mobile robots
Applied Intelligence
Distributed multi-robot coordination in area exploration
Robotics and Autonomous Systems
Distributed multi-robot coordination in area exploration
Robotics and Autonomous Systems
RTTES: Real-time search in dynamic environments
Applied Intelligence
Distributed Constraint Reasoning Applied to Multi-robot Exploration
ICTAI '09 Proceedings of the 2009 21st IEEE International Conference on Tools with Artificial Intelligence
Distributed Control of Robotic Networks: A Mathematical Approach to Motion Coordination Algorithms
Distributed Control of Robotic Networks: A Mathematical Approach to Motion Coordination Algorithms
An information-based exploration strategy for environment mapping with mobile robots
Robotics and Autonomous Systems
Multi-robot path finding with wireless multihop communications
IEEE Communications Magazine
Journal of Field Robotics
Formation preserving path finding in 3-D terrains
Applied Intelligence
Abstraction and control for Groups of robots
IEEE Transactions on Robotics
Tracking control for multi-agent consensus with an active leader and variable topology
Automatica (Journal of IFAC)
Hi-index | 0.00 |
A common assumption made in multi-robot research is the connectedness of the underlying network. Although this seems a valid assumption for static networks, it is not realistic for mobile robotic networks, where communication between robots usually is distance dependent. Motivated by this fact, we explicitly consider the communication limitations. This paper extends the LFIP based exploration framework previously developed by Pal et al. (Cogn. Comput. doi: 10.1007/s12559-012-9142-7 , 2012), to address the Multi-Agent Territory Exploration (MATE-n k ) task under severe communication constraints. In MATE-n k task agents have to explore their environment to find and visit n checkpoints, which only count as "visited" when k agents are present at the same time. In its simplest form, the architecture consists of two layers: an "Exploration layer" consisting of a selection of future locations for the team for further exploring the environment, and "Exploration and CheckpointVisit layer", consisting of visiting the detected checkpoints while continuing the exploration task. The connectivity maintenance objective is achieved via two ways: (1) The first layer employs a leader-follower concept, where a communication zone is constructed by the leader using a distance transforms method, and (2) In the second layer we make use of a graph theory for characterizing the communication, which employs the adjacency and Laplacian matrices of the graph and their spectral properties. The proposed approach has been implemented and evaluated in several simulated environments and with varying team sizes and communication ranges. Throughout the paper, our conclusions are corroborated by the results from extensive simulations.